In many processes for image processing or image pre-processing methods for motion estimation with respect to a sequence of images are applied. In these known methods based on predictor vectors so-called predictor vector updates are generated which are then applied to the predictor vector or predictor vector candidate in order to generate candidate vectors or candidate motion vectors. Such candidate vectors are then classified and a distinct candidate vector is chosen as a best one with respect to a certain criterion.
The crucial point is the conversions of such a process. Conversion performance, sub-pixel estimation, granularity, and the like can improved by increasing large numbers of updates which should be generated and applied to a given predictor vector. However, the computational burden increases with the number of updates which have to be applied to the predictor vector in order to create a larger number of candidates.